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The AI ​​model can use heart rhythm data to detect premature aging and cognitive decline
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The AI ​​model can use heart rhythm data to detect premature aging and cognitive decline

Bluebay2014/Istock via Getty Images
Bluebay2014/Istock via Getty Images

Electrocardiogram tests – which measure the electrical activity of the heart – can one day be linked to an artificial intelligence model to detect premature and cognitive decline, suggests new research.

The study found that people with accelerated ECG age had lower cognitive test results than those who experience normally aging. Preliminary results will be presented Wednesday at the American Stroke Association’s international stroke conference in Los Angeles. The results are regarded as preliminary until complete results are published in a peer-reviewed journal.

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“Unlike chronological age, which is based on years, ECG Age reflects the functional status of the heart and potentially the entire organism at the tissue level, which provides insights on aging and health status,” said main author Bernard Ofosuhene in a News notice. He is a clinical research coordinator at the Department of Medicine at Umass Chan Medical School in Worcester, Massachusetts.

Each time the heart beats it emits an electric impulse or wave. An ECG, also known as an ECG, translates these impulses into wavy lines on paper, which allows doctors to detect heart problems. For this study, researchers designed an AI model to predict a person’s biological age using their ECG data. Biological age reflects how a person’s cells and tissues can deteriorate.

Previous studies have shown that the ECG age can help predict heart disease and death. But little was known about its relationship with cognitive deterioration. The researchers note that since ECG is widely used in cardiovascular diagnoses, the new tool can help flag people with the risk of cognitive impairment.

In the study, researchers analyzed data from 63,800 participants in the British biobank, an ongoing investigation of more than 500,000 volunteers in the UK. The participants were aged 40 to 69 when they registered between 2006 and 2010. They had performed ECG and took a battery with cognitive tests during visits between August 2023 and July 2024. The AI ​​model was then applied to determine their ECG age.

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According to the AI ​​model, 15,563 participants were found to experience normal aging, 24,671 experienced accelerated aging and 23 566 experienced retarded aging. Compared to the normal aging group, the accelerated group showed a significant decline in cognitive performance, while those whose ECG suggested that they aged slower performed better on the tests.

Based on the ECG age, those who were younger than their chronological age group surpassed their comrades on six out of eight cognitive tests, while with an older ECG age, they managed worse on six tests.

“There are many ECG tasks available for stroke treatment, and I encourage healthcare personnel to use this information to look for signs of cognitive decline,” said Ofosuhene. “To do that can help with early diagnosis and rapid intervention.”

Future studies would investigate whether gender could affect the link between ECG age and cognitive performance, he said. Since most British biobank participants are of white European ancestors, Ofosuhene said that his team would like to determine whether their results can be replicated in more different populations.

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The study adds a growing amount of research that recognizes “the strong link between heart and brain health,” says Dr. Fernando D. Testai in the news message. Testai, professor of neurology and rehabilitation at the University of Illinois College of Medicine in Chicago, led the Writing Committee for a 2024 American Heart Association scientific statement on the connection between common cardiovascular disease and cognitive deterioration.

Testai, which was not involved in the study, said that the use of ECG data to assess cognitive ability may seem like “a futuristic idea”, but validation of the study can have several important results. The ECG tasks collected at a doctor’s office or at a distance with portable, for example, can help to assess cognition at home or in the countryside that lacks neuropsychiatric specialists, he said. Using data and AI can also be faster and more objective than traditional assessments.

“But an important issue remains,” Testai said. “Can ECG -Data predict future cognitive decline? To answer that this can lead to valuable treatments.”

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American Heart Association News Covers heart and brain health. Not all opinions expressed in this story reflects the official position of the American Heart Association. Copyright is owned or held by the American Heart Association, Inc., and all rights are reserved.